scholarly journals Mental health and school absenteeism in children with long‐term physical conditions: A secondary analysis of the British Child and Adolescent Mental Health Surveys 2004 and 2007

2021 ◽  
Author(s):  
Katie Finning ◽  
Irida Neochoriti Varvarrigou ◽  
Tamsin Ford ◽  
Laura Panagi ◽  
Obioha C. Ukoumunne
Keyword(s):  
Mental Health ◽  
Health Surveys ◽  
Secondary Analysis ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
School Absenteeism ◽  
Physical Conditions

The relationship between exclusion from school and mental health: a secondary analysis of the British Child and Adolescent Mental Health Surveys 2004 and 2007

2017 ◽  
Vol 48 (4) ◽  
pp. 629-641 ◽  
Author(s):  
T. Ford ◽  
C. Parker ◽  
J. Salim ◽  
R. Goodman ◽  
S. Logan ◽  
...  
Keyword(s):  
Mental Health ◽  
Psychological Distress ◽  
Psychiatric Disorder ◽  
Health Surveys ◽  
Secondary Analysis ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
The Impact ◽  
The Relationship

BackgroundChildren with poor mental health often struggle at school. The relationship between childhood psychiatric disorder and exclusion from school has not been frequently studied, but both are associated with poor adult outcomes. We undertook a secondary analysis of the British Child and Adolescent Mental Health Surveys from 2004 and its follow-up in 2007 to explore the relationship between exclusion from school and psychopathology. We predicted poorer mental health among those excluded.MethodPsychopathology was measured using the Strengths and Difficulties Questionnaire, while psychiatric disorder was assessed using the Development and Well-Being Assessment and applying Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM IV) criteria. Exclusion from school and socio-demographic characteristics were reported by parents. Multi-variable regression models were used to examine the impact of individual factors on exclusion from school or psychological distress.ResultsExclusion from school was commoner among boys, secondary school pupils and those living in socio-economically deprived circumstances. Poor general health and learning disability among children and poor parental mental health were also associated with exclusion. There were consistently high levels of psychological distress among those who had experienced exclusion at baseline and follow-up.ConclusionsWe detected a bi-directional association between psychological distress and exclusion. Efforts to identify and support children who struggle with school may therefore prevent both future exclusion and future psychiatric disorder.

The Long-Term Effects of Breastfeeding on Child and Adolescent Mental Health: A Pregnancy Cohort Study Followed for 14 Years

2010 ◽  
Vol 156 (4) ◽  
pp. 568-574 ◽  
Author(s):  
Wendy H. Oddy ◽  
Garth E. Kendall ◽  
Jianghong Li ◽  
Peter Jacoby ◽  
Monique Robinson ◽  
...  
Keyword(s):  
Mental Health ◽  
Cohort Study ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
Long Term Effects ◽  
Pregnancy Cohort

scholarly journals Local, Early, and Precise: Designing a Clinical Decision Support System for Child and Adolescent Mental Health Services

2020 ◽  
Vol 11 ◽  
Author(s):  
Thomas Brox Røst ◽  
Carolyn Clausen ◽  
Øystein Nytrø ◽  
Roman Koposov ◽  
Bennett Leventhal ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Health Services ◽  
Health Services ◽  
Clinical Decision ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
Mental Health Disorders ◽  
Evidence Based ◽  
Health Disorders

Mental health disorders often develop during childhood and adolescence, causing long term and debilitating impacts at individual and societal levels. Local, early, and precise assessment and evidence-based treatment are key to achieve positive mental health outcomes and to avoid long-term care. Technological advancements, such as computerized Clinical Decision Support Systems (CDSSs), can support practitioners in providing evidence-based care. While previous studies have found CDSS implementation helps to improve aspects of medical care, evidence is limited on its use for child and adolescent mental health care. This paper presents challenges and opportunities for adapting CDSS design and implementation to child and adolescent mental health services (CAMHS). To highlight the complexity of incorporating CDSSs within local CAMHS, we have structured the paper around four components to consider before designing and implementing the CDSS: supporting collaboration among multiple stakeholders involved in care; optimally using health data; accounting for comorbidities; and addressing the temporality of patient care. The proposed perspective is presented within the context of the child and adolescent mental health services in Norway and an ongoing Norwegian innovative research project, the Individualized Digital DEcision Assist System (IDDEAS), for child and adolescent mental health disorders. Attention deficit hyperactivity disorder (ADHD) among children and adolescents serves as the case example. The integration of IDDEAS in Norway intends to yield significantly improved outcomes for children and adolescents with enduring mental health disorders, and ultimately serve as an educational opportunity for future international approaches to such CDSS design and implementation.

scholarly journals Testing an individualized digital decision assist system for the diagnosis and management of mental and behavior disorders in children and adolescents

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Carolyn E. Clausen ◽  
Bennett L. Leventhal ◽  
Øystein Nytrø ◽  
Roman Koposov ◽  
Odd Sverre Westbye ◽  
...  
Keyword(s):  
Mental Health ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
Mental Health Disorders ◽  
Diagnosis And Treatment ◽  
Health Disorders

Abstract Background Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long-term disability. In Norway, approximately 20% of all children and adolescents are experiencing mental health problems. To address this, health officials in Norway have called for the integration of innovative approaches. A clinical decision support system (CDSS) is an innovative, computer-based program that provides health professionals with clinical decision support as they care for patients. CDSS use standardized clinical guidelines and big data to provide guidance and recommendations to clinicians in real-time. IDDEAS (Individualised Digital DEcision Assist System) is a CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS). Methods/design IDDEAS is a mixed-methods innovation and research project, which consists of four stages: 1) Assessment of Needs and Preparation of IDDEAS; 2) The Development of IDDEAS CDSS Model; 3) The Evaluation of the IDDEAS CDSS; and, 4) Implementation & Dissemination. Both qualitative and quantitative methods will be used for the evaluation of IDDEAS CDSS model. Child and adolescent psychologists and psychiatrists (n = 30) will evaluate the IDDEAS` usability, acceptability and relevance for diagnosis and treatment of attention-deficit/hyperactivity disorder. Discussion The IDDEAS CDSS model is the first guidelines and data-driven CDSS to improve efficiency of diagnosis and treatment of child and adolescent mental health disorders in Norway. Ultimately, IDDEAS will help to improve patient health outcomes and prevent long-term adverse outcomes by providing each patient with evidence-based, customized clinical care. Trial registration ISRCTN, ISRCTN12094788. Ongoing study, registered prospectively 8 April 2020 10.1186/ISRCTN12094788

scholarly journals How accurate are teachers’ assessments of children’s mental health?

2020 ◽  
Keyword(s):  
Mental Health ◽  
Mental Disorder ◽  
Health Survey ◽  
School Children ◽  
Secondary Analysis ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
Children’S Mental Health ◽  
Children's Mental Health ◽  
Mental Health Survey

Frances Mathews, Tamsin Ford and colleagues have performed a secondary analysis of the 2004 British Child and Adolescent Mental Health Survey, to understand how accurately teacher concern predicts the presence of a mental disorder in school children.

scholarly journals Are children with unrecognised psychiatric disorders being excluded from school? A secondary analysis of the British Child and Adolescent Mental Health Surveys 2004 and 2007

2018 ◽  
Vol 49 (15) ◽  
pp. 2561-2572 ◽  
Author(s):  
Claire Parker ◽  
María Tejerina-Arreal ◽  
William Henley ◽  
Robert Goodman ◽  
Stuart Logan ◽  
...  
Keyword(s):  
Mental Health ◽  
Secondary Analysis ◽  
Well Being ◽  
Adolescent Mental Health ◽  
Child And Adolescent ◽  
Logistic Regression Models ◽  
Adjusted Logistic Regression ◽  
Teachers And Parents ◽  
Impact Supplement ◽  
The Impact

AbstractBackgroundThere is limited research that explores the association between exclusion from school and mental health, but it seems intuitively plausible that the recognition of mental difficulties by key teachers and parents would influence the likelihood of exclusion from school.MethodsA secondary analysis of the British Child and Adolescent Mental Health survey 2004, (n = 7997) and the 2007 follow-up (n = 5326) was conducted. Recognition of difficulty was assessed via a derived variable that combined the first item of the Impact supplement of the Strengths and Difficulties Questionnaire which asked parents and teachers if they thought that the child has difficulties with emotions, behaviour and concentration, and the presence/absence of psychiatric disorder measured by the Development and Well-being Assessment.ResultsAdjusted logistic regression models demonstrated that children with recognised difficulties were more likely to be excluded [adjusted odds ratio (OR) 5.78, confidence interval 3.45–9.64, p < 0.001], but children with unrecognised difficulties [adjusted OR 3.58 (1.46–8.81) p < 0.005] or recognised subclinical difficulties [adjusted OR 3.42 (2.04–5.73) p < 0.001] were also more likely to be excluded than children with no difficulties. Children with conduct disorder and attention deficit hyperactivity disorder were most likely to be excluded compared with other types of disorder.ConclusionExclusion from school may result from a failure to provide timely and effective support rather than a failure to recognise psychopathology.

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